About Bazaarvoice
At Bazaarvoice, we create smart shopping experiences. Through our expansive global network, product-passionate community & enterprise technology, we connect thousands of brands and retailers with billions of consumers. Our solutions enable brands to connect with consumers and collect valuable user-generated content, at an unprecedented scale. This content achieves global reach by leveraging our extensive and ever-expanding retail, social & search syndication network. And we make it easy for brands & retailers to gain valuable business insights from real-time consumer feedback with intuitive tools and dashboards. The result is smarter shopping: loyal customers, increased sales, and improved products.
The problem we are trying to solve : Brands and retailers struggle to make real connections with consumers. It's a challenge to deliver trustworthy and inspiring content in the moments that matter most during the discovery and purchase cycle. The result? Time and money spent on content that doesn't attract new consumers, convert them, or earn their long-term loyalty.
Our brand promise : closing the gap between brands and consumers.
Founded in 2005, Bazaarvoice is headquartered in Austin, Texas with offices in North America, Europe, Asia and Australia.
Key Responsibilities
Design, implement, and maintain robust MLOps platforms and tooling for both batch and streaming ML pipelines.Develop and manage monitoring and observability solutions for ML systems.Follow DevOps practices, including CI/CD pipelines and Infrastructure as Code (IaC).Implement cloud-based solutions on AWS (or similar public cloud providers).Collaborate with ML Engineers and Data Scientists to develop, train, and deploy machine learning models.Engage in feature engineering and model optimization to improve ML system performance.Participate in the full ML lifecycle, from data preparation to model deployment and monitoring.Optimize and refactor existing systems for improved performance and reliability.
Participate in technical initiatives and best practices in both MLOps and ML Engineering. Strong Python Proficiency:
Excellent skills for developing, deploying, and maintaining our machine learning systems. Language Versatility: 3+ Years of Experience with statically-typed or JVM languages. Willingness to learn Scala is highly desirable.
Cloud Engineering Skills: 3+ years experience with Cloud Platforms & Services, ideally AWS (e.g., Lambda, ECS, ECR, CloudWatch, MSK, SNS, SQS).
Infrastructure as Code: Beginner- or intermediate-level proficiency in IaC, particularly Terraform.
Kubernetes Expertise: 3+ years of hands-on experience with managing clusters and deploying services. Data Orchestration: 3+ years of Experience with ML orchestration tools (e.g., Flyte, Airflow, Kubeflow, Luigi, or Prefect). CI/CD: 3+ Years of Expertise in pipelines, especially GitHub Actions and Jenkins.
Networking: Knowledge of concepts and implementation.
Streaming: Experience with Kafka and other streaming technologies.
ML Monitoring: Familiarity with observability tools (e.g., Arize AI, Weights and Biases).
NLP/LLMs: Experience with NLP, LLMs, and RAG systems in production, or strong desire to learn.
CLI & Shell Scripting: Proficiency in scripting and command-line tools.
APIs: Experience with deploying and managing production APIs.
Software Engineering Best-Practices: Knowledge of industry standards and practices.
Preferred Qualifications
AWS AI Services: Hands-on experience with AWS SageMaker and/or AWS Bedrock.
Data Processing: Experience with high-volume, unstructured data processing.
ML Applications: Familiarity with NLP, Computer Vision, and traditional ML applications.
System Migration: Previous work in refactoring and migrating complex systems.
AWS Certification: AWS Solution Architect Professional or Associate certification.Personal QualitiesPassionate about building developer-friendly platforms and tools.Thrives in a terminal-based development environment.Enthusiastic about creating production-grade, robust, reliable, and performant systems.Not afraid to dive into and improve complex existing solutions.Team player who works well with ML Engineers, Data Scientists, and management.Good problem-solving and communication skills.
#LI-Hybrid#LI-PC1
Why join Bazaarvoice?
Customer is key
We see our own success through our customers’ outcomes.
We approach every situation with a customer first mindset.
Transparency & Integrity Builds Trust
We believe in the power of authentic feedback because it’s in our DNA.
We do the right thing when faced with hard choices. Transparency and trust accelerate our collective performance.
Passionate Pursuit of Performance
Our energy is contagious, because we hire for passion, drive & curiosity.
We love what we do, and because we’re laser focused on our mission.
Innovation over Imitation
We seek to innovate as we are not content with the status quo.
We embrace agility and experimentation as an advantage.
Stronger Together
We bring our whole selves to the mission and find value in diverse perspectives.
We champion what’s best for Bazaarvoice before individuals or teams.
As a stronger company we build a stronger community.
Commitment to diversity and inclusion
Bazaarvoice provides equal employment opportunities (EEO) to all team members and applicants according to their experience, talent, and qualifications for the job without regard to race, color, national origin, religion, age, disability, sex (including pregnancy, gender stereotyping, and marital status), sexual orientation, gender identity, genetic information, military/veteran status, or any other category protected by federal, state, or local law in every location in which the company has facilities. Bazaarvoice believes that diversity and an inclusive company culture are key drivers of creativity, innovation and performance. Furthermore, a diverse workforce and the maintenance of an atmosphere that welcomes versatile perspectives will enhance our ability to fulfill our vision of creating the world’s smartest network of consumers, brands, and retailers.